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Review
. 2023 May:83:104642.
doi: 10.1016/j.bspc.2023.104642. Epub 2023 Feb 10.

Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives

Amir Rehman  1 , Huanlai Xing  1 , Muhammad Adnan Khan  2   3 , Mehboob Hussain  1 , Abid Hussain  1 , Nighat Gulzar  4
Affiliations
Review

Emerging technologies for COVID (ET-CoV) detection and diagnosis: Recent advancements, applications, challenges, and future perspectives

Amir Rehman et al. Biomed Signal Process Control. 2023 May.

Abstract

In light of the constantly changing terrain of the COVID outbreak, medical specialists have implemented proactive schemes for vaccine production. Despite the remarkable COVID-19 vaccine development, the virus has mutated into new variants, including delta and omicron. Currently, the situation is critical in many parts of the world, and precautions are being taken to stop the virus from spreading and mutating. Early identification and diagnosis of COVID-19 are the main challenges faced by emerging technologies during the outbreak. In these circumstances, emerging technologies to tackle Coronavirus have proven magnificent. Artificial intelligence (AI), big data, the internet of medical things (IoMT), robotics, blockchain technology, telemedicine, smart applications, and additive manufacturing are suspicious for detecting, classifying, monitoring, and locating COVID-19. Henceforth, this research aims to glance at these COVID-19 defeating technologies by focusing on their strengths and limitations. A CiteSpace-based bibliometric analysis of the emerging technology was established. The most impactful keywords and the ongoing research frontiers were compiled. Emerging technologies were unstable due to data inconsistency, redundant and noisy datasets, and the inability to aggregate the data due to disparate data formats. Moreover, the privacy and confidentiality of patient medical records are not guaranteed. Hence, Significant data analysis is required to develop an intelligent computational model for effective and quick clinical diagnosis of COVID-19. Remarkably, this article outlines how emerging technology has been used to counteract the virus disaster and offers ongoing research frontiers, directing readers to concentrate on the real challenges and thus facilitating additional explorations to amplify emerging technologies.

Keywords: Bibliometric analysis; CiteSpace; Detection; Emerging technologies; Network visualization; SARS-COVID-2.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

None
Graphical abstract
Fig. 1
Fig. 1
Statistics on COVID-19 fatality rates among the top 12 afflicted countries were last updated in November 2022.
Fig. 2
Fig. 2
The flow diagram of the bibliometric review methods that were implemented.
Fig. 3
Fig. 3
(a) The rising trend of SARS-COVID-2 publications (b) The most productive collaborative countries in boosting ET-CoV research.
Fig. 4
Fig. 4
Top research areas are distributed according to subject wise.
Fig. 5
Fig. 5
Co-authorship institution network analysis plotting in CiteSpace.
Fig. 6
Fig. 6
Co-authorship Country network analysis plotting in CiteSpace.
Fig. 7
Fig. 7
Visualization of document co-citation analysis in CiteSpace.
Fig. 8
Fig. 8
Journal co-citation network analysis CiteSpace plotting.
Fig. 9
Fig. 9
CiteSpace visualization of keyword co-occurrence analysis.
Fig. 10
Fig. 10
Top thirteen co-occurring keywords clusters of ET-CoV related research.
Fig. 11
Fig. 11
Various applications of emerging technologies for SARS-COV-2 detection.
Fig. 12
Fig. 12
The contribution of IoMT devices in (point of care) POC diagnoses to combat COVID-19.
Fig. 13
Fig. 13
Conceptual proposal for smart city.
See this image and copyright information in PMC

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